Variational modal decomposition high-voltage switchgear signal denoising method and system

Abstract

The application discloses a variational mode decomposition high-voltage switchgear signal denoising method and system, which comprises the following steps: firstly, collecting the mechanical signal of the high-voltage switchgear; then, performing self-adaptive global optimization on the key parameters of the variational mode decomposition by using an improved sparrow search algorithm, wherein the improved strategy comprises chaotic disturbance reverse learning initialization, dynamic step control and Levy flight mechanism; then, performing variational mode decomposition on the signal by using the optimized parameters to obtain a series of intrinsic mode function components; then, screening the effective components by calculating the Pearson correlation coefficients of the components and the original signal; finally, reconstructing the effective components to obtain the denoised signal. The application overcomes the problems of blind parameter setting, mode aliasing and serious noise residue in the traditional method, and can adaptively realize high-precision signal denoising, significantly improves the signal-to-noise ratio and waveform fidelity, effectively retains the fault characteristics, and provides a reliable data basis for accurate fault diagnosis of the high-voltage switchgear.

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